Syst. Biol. 45(1):1--26, 1996

1 Department of Biology, Washington University,

St. Louis, Missouri 63130-4899, USA

2 Department of Biological Sciences, University of South Alabama,

Mobile, Alabama 36688, USA

3 Present address: Department of Zoology, Brigham Young University,

Provo, Utah 84602, USA.

E-mail: crandall@acd1.byu.edu.

Abstract.---The use of comparative methods to test evolutionary hypotheses
has become more common at both the macro- and microevolutionary levels. The
application of such techniques is especially troublesome at the interface of
these levels because phylogenetic relationships are often difficult to
estimate. The use of a technique developed to estimate intraspecific
cladograms combined with more traditional methods of phylogenetic estimation
can improve the estimate in data sets containing a range of diversity when
the lower bound of the range approaches 0% divergence. For nucleotide
sequence data from the 16S region of the mitochondrial DNA from 72
individuals representing 37 species, this combined-procedures approach
improved the estimate of phylogenetic relationships using maximum-parsimony,
maximum-likelihood, and neighbor-joining methods. The estimated trees were
used to examine systematic hypotheses relating to the crayfish genus
Orconectes and species relationships within the subgenus Procericambarus. The
monophyly of Procericambarus is not supported by the mitochondrial data, and
the hypotheses of unique origins of various morphological features previously
used in determining crayfish relationships is unsupported.

[Crayfish;
mitochondrial DNA; molecular systematics; parsimony; phylogeny
reconstruction; Orconectes.]

Syst. Biol. 45(1):27--47, 1996

Department of Zoology, University of Wisconsin,

Madison, Wisconsin 53706-1381, USA

1 E-mail: rdiaz@macc.wisc.edu

2 E-mail: tgarland@macc.wisc.edu

Abstract.---We examined the statistical performance (in terms of type I error
rates) of Felsenstein's (1985, Am. Nat. 125:1--15) comparative method of
phylogenetically independent contrasts for testing hypotheses about
evolutionary correlations of continuous-valued characters. We simulated data
along two different phylogenies, one for 15 species of plethodontid
salamanders and the other for 49 species of Carnivora and ungulates. We
implemented 15 different models of character evolution, 14 of which deviated
from Brownian motion, which is in effect assumed by the method. The models
studied included the Ornstein--Uhlenbeck process and punctuated equilibrium
(change allowed in only one daughter at each bifurcation) both with and
without trends and limits on how far phenotypes could evolve. As has been
shown in several previous simulation studies, a nonphylogenetic Pearson
correlation of species' mean values yielded inflated type I error rates under
most models, including that of simple Brownian motion. Independent contrasts
yielded acceptable type I error rates under Brownian motion (and in
preliminary studies under slight deviations from this model), but they were
inflated under most other models. This new result confirms the model
dependence of independent contrasts. However, when branch lengths were
checked and transformed, then type I error rates of independent contrasts
were reduced. Moreover, the maximum observed type I error rates never
exceeded twice the nominal P value at a = 0.05. In comparison, the
nonphylogenetic correlation tended to yield extremely inflated (and highly
variable) type I error rates. These results constitute another demonstration
of the general superiority of phylogenetically based statistical methods over
nonphylogenetic ones, even under extreme deviations from a Brownian motion
model. These results also show the necessity of checking the assumptions of
statistical comparative methods and indicate that diagnostic checks and
remedial measures can substantially improve the performance of the
independent contrasts method.

[Comparative method; computer
simulation;independent contrasts; phylogeny; hypothesis testing; statistics;
correlated evolution.]

Syst. Biol. 45(1):48--66, 1996

Virginia Institute of Marine Science, School of Marine Science,

The College of William and Mary,

Gloucester Point, Virginia 23062, USA;

E-mail: mes@vims.edu

Abstract.---The correlation that exists among multiple cladograms is often
taken as evidence of some underlying macroevolutionary phenomenon common to
the histories of those clades and, thus, as an explanation of the patterns of
association of the constituent taxa. Such studies have various forms, the
most common of which are cladistic biogeography and host--parasite
coevolution. The issue of confidence has periodically been a theoretical
consideration of vicariance biogeographers but in practice has been largely
ignored by others. Previous approaches to assessing confidence in historical
associations are examined here in relation to the difference between
simple-event and cumulative probabilities and in relation to the
restrictiveness of joint hypothesis testing. The phylogenetic covariance
probability (PCP) test, a novel approach to assessing confidence in
hypotheses of historical association, employs the empirical protocol of
Brooks parsimony analysis (BPA) in an iterative, computer-intensive
randomization routine. The PCP value consists of the frequency with which a
solution as efficient or more efficient than the observed hypothesis of
correlated phylogeny is achieved with random associations (e.g., of parasites
and hosts or of taxa and areas). Because only the associations, and not the
contributing phylogenies, are subjected to randomization, the test is not
prone to certain criticisms leveled at other cladistic randomization
routines. The behavior of the PCP test is examined in relation to eight
published studies of historical association. This test is appropriately
sensitive to the degrees of freedom allowed by the number of contributing
clades and the number of taxa in those clades, to the extent of noncorrelated
associations in the observed hypothesis, and to the relative information
content contributing to that hypothesis.

[Biogeography; BPA; coevolution;
confidence; historical associations; randomization.]

Syst. Biol. 45(1):67--78, 1996

1 Doctoral Program in Anthropological Sciences, State University of New York,

Stony Brook, New York 11794-4364, USA

2 Department of Mathematics, City University of New York,

Flushing, New York 11367, USA

3 E-mail: dstrait@ccvm.sunysb.edu.

Abstract.---Finite mixture coding (FMC) is a new method of coding continuous
characters. FMC uses a three-step goodness-of-fit procedure to assign codes.
First, for a given measurement, parameters are estimated for a number of
density functions that describe a data set either of species means or of
measurements of specimens from several species. The density functions
represent either a single population or a mixture of populations (e.g., a
mixture of two normal distributions). Next, a goodness-of-fit criterion (the
Akaike information criterion) is used to determine which of the density
functions best describes the data set. The best function indicates the number
of populations into which the variates of the data set can be segregated.
Finally, species are assigned to the population for which its probability of
membership is highest. Each population is then assigned a code, and species
falling within the same population share the same code. Although other coding
methods incorporate statistical tests or parameters into the coding process,
FMC is the only method that produces codes as the direct output of a
statistical procedure.

[Code; continuous character; finite mixture analysis;
likelihood estimation; cladistics.]

Syst. Biol. 45(1):79--91, 1996

Department of Community Medicine, University of Cambridge, Institute of Public Health, Forvie, Robinson Way, Cambridge CB2 2SR, England

Abstract.---The method of minimum evolution was introduced by Edwards and
Cavalli-Sforza (1963, Heredity 18:553, Ann. Hum. Genet. 27:104--105) for the
reconstruction of phylogenetic trees. Its relationship to the subsequently
developed parsimony methods and the logical basis of the methods are
discussed, with special reference to probability models. The minimum
evolution method did not derive from Hennig's phylogenetic systematics but
rather as an approximation to the maximum-likelihood solution for a model of
random evolution.

[Phylogenetic trees; minimum evolution; Darwin principle;
Ockham's razor; parsimony.]

Syst. Biol. 45(1):92--98, 1996

1 Department of Integrative Biology, University of California,

Berkeley, California 94720, USA;

E-mail: johnh@mws4.biol.berkeley.edu

2 Department of Zoology, University of Texas, Austin, Texas 78712, USA;

E-mail: bull@bull.zo.utexas.edu

Abstract.---Molecular data are commonly used to reconstruct the evolutionary
histories of organisms. However, evolutionary reconstructions from different
molecular data sets sometimes conflict. It is generally unknown whether these
different estimates of history result from random variation in the processes
of nucleotide substitution or from fundamentally different evolutionary
mechanisms underlying the histories of the genes analyzed. We describe a
novel likelihood ratio test that compares different topologies (each
estimated from a different data partition for the same taxa) to determine if
they are significantly different. The results of this test indicate that
different genes provide significantly different phylogenies for amniotes,
supporting earlier suggestions based on less direct tests. These results
suggest that some molecular data can give misleading information about
evolutionary history.

[Likelihood ratio test; maximum likelihood;
phylogenetic methods; phylogenetic heterogeneity.]

Syst. Biol. 45(1):99--110, 1996

Department of Biological Sciences, University of New Orleans,

New Orleans, Louisiana 70148, USA;

E-mail: jsrbs@uno.edu

Abstract.---Several recent studies have included attempts to use the balance
of phylogenetic trees, i.e., the extent to which sister groups within a tree
tend to be the same size, to test hypotheses about the macroevolutionary
processes that produced them. Such tests require measures of balance or
imbalance and the moments or probability distributions of these measures
under some null models. In earlier work, I developed recursion equations for
the mean, variance, skewness, and complete probability distribution of
Colless's coefficient of imbalance (I) (Rogers, 1994, Evolution
48:2026--2036). In this paper, I report the extension of these techniques to
two additional imbalance measures, the number of unbalanced nodes on a tree
(J) and Sackin's index (K), under both the equal-rates Markov (ERM) model and
the equal probability (EP) model. I also show how to find the correlations
and joint probability distributions of all pairs of these three coefficients.
I and K are so highly correlated for trees of all sizes that K contains
little additional information about tree balance that is not conveyed by I.
The correlation of I and J, however, decreases rapidly with increasing tree
size, indicating that the testing of macroevolutionary hypotheses may be
refined by employing the joint distribution of these two coefficients. The
results of two simulation studies of non-ERM speciation processes are used to
illustrate how the joint distribution of I and J may be used.

[Phylogenetic
trees; macroevolutionary processes; speciation; tree imbalance coefficients;
probability distributions.]